predict {remote} | R Documentation |
EOT based spatial prediction
Description
Make spatial predictions using the fitted model returned by
eot()
. A (user-defined) set of n modes will be used to
model the outcome using the identified link functions of the respective modes
which are added together to produce the final prediction.
Usage
## S4 method for signature 'EotStack'
predict(object, newdata, n = 1, cores = 1L, filename = "", ...)
## S4 method for signature 'EotMode'
predict(object, newdata, n = 1, cores = 1L, filename = "", ...)
Arguments
object |
an |
newdata |
the data to be used as predictor |
n |
the number of modes to be used for the prediction.
See |
cores |
|
filename |
|
... |
further arguments passed to |
Value
a RasterStack of nlayers(newdata)
See Also
raster::calc()
, raster::writeRaster()
.
Examples
### not very useful, but highlights the workflow
data(pacificSST)
data(australiaGPCP)
## train data using eot()
train <- eot(x = pacificSST[[1:10]],
y = australiaGPCP[[1:10]],
n = 1)
## predict using identified model
pred <- predict(train,
newdata = pacificSST[[11:20]],
n = 1)
## compare results
opar <- par(mfrow = c(1,2))
plot(australiaGPCP[[13]], main = "original", zlim = c(0, 10))
plot(pred[[3]], main = "predicted", zlim = c(0, 10))
par(opar)
[Package remote version 1.2.3 Index]